Electroretinography Reveals Difference in Cone Function between Syndromic and Nonsyndromic USH2A Patients

Usher syndrome is an inherited and irreversible disease that manifests as retinitis pigmentosa (RP) and bilateral neurosensory hearing loss. Mutations in Usherin 2A (USH2A) are not only a frequent cause of Usher syndrome, but also nonsyndromic RP. Although gene-and cell-based therapies are on the horizon for RP and Usher syndrome, studies characterizing natural disease are lacking. In this retrospective analysis, retinal function of USH2A patients was quantified with electroretinography. Both groups had markedly reduced rod and cone responses, but nonsyndromic USH2A patients had 30 Hz-flicker electroretinogram amplitudes that were significantly higher than syndromic patients, suggesting superior residual cone function. There was a tendency for Usher syndrome patients to have a higher distribution of severe mutations, and alleles in this group had a higher odds of containing nonsense or frame-shift mutations. These data suggest that the previously reported severe visual phenotype seen in syndromic USH2A patients could relate to a greater extent of cone dysfunction. Additionally, a genetic threshold may exist where mutation burden relates to visual phenotype and the presence of hearing deficits. The auditory phenotype and allelic hierarchy observed among patients should be considered in prospective studies of disease progression and during enrollment for future clinical trials.National Institute of HealthNational Cancer InstituteResearch to Prevent Blindness (RPB)RPB, New York, NY, USARPBInternational Council of Ophthalmology - Retina Research FoundationNIHTistou and Charlotte Kerstan FoundationSchneeweiss Stem Cell Fund, New York StateFoundation Fighting Blindness New York Regional Research CenterCrowley Family FundGebroe Family FoundationColumbia Univ, Dept Ophthalmol, Med Ctr, Jonas Childrens Vis Care, New York, NY 10027 USAColumbia Univ, Dept Ophthalmol, Med Ctr, Bernard & Shirlee Brown Glaucoma Lab, New York, NY 10027 USANew York Presbyterian Hosp, Edward S Harkness Eye Inst, New York, NY 10034 USASuny Downstate Med Ctr, Brooklyn, NY 11203 USAUniv Fed Espirito Santo, Dept Ophthalmol, Vitoria, BrazilUniv Fed Sao Paulo, Dept Ophthalmol, Sao Paulo, BrazilColumbia Univ, Dept Biostat, New York, NY USAUniv Montreal, Dept Ophthalmol, Montreal, PQ, CanadaShanghai Jiao Tong Univ, Sch Med, Xin Hua Hosp, Dept Ophthalmol, Shanghai, Peoples R ChinaColumbia Univ, Inst Human Nutr, Dept Pathol & Cell Biol, Stem Cell Initiat CSCI,Coll Phys & Surg, New York, NY 10032 USAStanford Univ, Dept Ophthalmol, Om Lab, Byers Eye Inst, Palo Alto, CA 94304 USAUniv Fed Sao Paulo, Dept Ophthalmol, Sao Paulo, BrazilWeb of Scienc

Finding needles in haystacks:Linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

OBILJEŽJA POČINITELJA NASILNIČKIH DELIKATA NA PODRUČJU PRIMORSKO-GORANSKE ŽUPANIJE OBZIROM NA POVRAT

Availability of sophisticated statistical modelling for developing robust reference equations has improved interpretation of lung function results. In 2012, the Global Lung function Initiative(GLI) published the first global all-age, multi-ethnic reference equations for spirometry but these lacked equations for those originating from the Indian subcontinent (South-Asians). The aims of this study were to assess the extent to which existing GLI-ethnic adjustments might fit South-Asian paediatric spirometry data, assess any similarities and discrepancies between South-Asian datasets and explore the feasibility of deriving a suitable South-Asian GLI-adjustment. Methods: Spirometry datasets from South-Asian children were collated from four centres in India and five within the UK. Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n=110). Results: Following exclusions, cross-sectional data were available from 8,124 children (56.3% male; 5-17 years). When compared with GLI-predicted values from White Europeans, forced expired volume in 1s (FEV1) and forced vital capacity (FVC) in South-Asian children were on average 15% lower, ranging from 4-19% between centres. By contrast, proportional reductions in FEV1 and FVC within all but two datasets meant that the FEV1/FVC ratio remained independent of ethnicity. The ‘GLI-Other’ equation fitted data from North India reasonably well while ‘GLI-Black’ equations provided a better approximation for South-Asian data than the ‘GLI-White’ equation. However, marked discrepancies in the mean lung function z-scores between centres especially when examined according to socio-economic conditions precluded derivation of a single South-Asian GLI-adjustment. Conclusion: Until improved and more robust prediction equations can be derived, we recommend the use of ‘GLI-Black’ equations for interpreting most South-Asian data, although ‘GLI-Other’ may be more appropriate for North Indian data. Prospective data collection using standardised protocols to explore potential sources of variation due to socio-economic circumstances, secular changes in growth/predictors of lung function and ethnicities within the South-Asian classification are urgently required

Finding needles in haystacks : linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201